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This paper presents a new technique for implementing a low-power CMOS imager with simultaneous on-chip computation of the difference and sum of two successive frames.
This paper presents a new technique for implementing a low-power CMOS imager with simultaneous on-chip computation of the difference and summ of two successive frames.
A variable resolution CMOS active pixel image sensor that enhances S/N ratio at low illumination level is presented.
Low-power, high-speed, accurate computation of centroid from a pre-defined window in the image plane is important for a number of space-based and commercial applications.
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Underwater video cameras of a proposed type (and, optionally, their light sources) would not be housed in pressure vessels. Conventional underwater cameras and their light sources are housed in pods that keep the contents dry and maintain interior pressures of about 1 atmosphere (.0.1 MPa). Pods strong enough to withstand the pressures at great ocean depths are bulky, heavy, and expensive. Elimination of the pods would make it possible to build camera/light-source units that would be significantly smaller, lighter, and less expensive. The depth ratings of the proposed camera/light source units would be essentially unlimited because the strengths of their housings would no longer be an issue. A camera according to the proposal would contain an active-pixel image sensor and readout circuits, all in the form of a single silicon-based complementary metal oxide/semiconductor (CMOS) integrated- circuit chip. As long as none of the circuitry and none of the electrical leads were exposed to seawater, which is electrically conductive, silicon integrated- circuit chips could withstand the hydrostatic pressure of even the deepest ocean. The pressure would change the semiconductor band gap by only a slight amount . not enough to degrade imaging performance significantly. Electrical contact with seawater would be prevented by potting the integrated-circuit chip in a transparent plastic case. The electrical leads for supplying power to the chip and extracting the video signal would also be potted, though not necessarily in the same transparent plastic. The hydrostatic pressure would tend to compress the plastic case and the chip equally on all sides; there would be no need for great strength because there would be no need to hold back high pressure on one side against low pressure on the other side. A light source suitable for use with the camera could consist of light-emitting diodes (LEDs). Like integrated- circuit chips, LEDs can withstand very large hydrostatic pressures. If power-supply regulators or filter capacitors were needed, these could be attached in chip form directly onto the back of, and potted with, the imager chip. Because CMOS imagers dissipate little power, the potting would not result in overheating. To minimize the cost of the camera, a fixed lens could be fabricated as part of the plastic case. For improved optical performance at greater cost, an adjustable glass achromatic lens would be mounted in a reservoir that would be filled with transparent oil and subject to the full hydrostatic pressure, and the reservoir would be mounted on the case to position the lens in front of the image sensor. The lens would by adjusted for focus by use of a motor inside the reservoir (oil-filled motors already exist).
In this paper, an ultra-fast smart vision system-on-a-chip design is proposed to provide effective solutions for real time machine vision applications by taking advantages of recent advances in integrated sensing/processing designs, electronic neural networks, advanced microprocessors and sub-micron VLSI technology.
Space-based gamma-ray telescopes such as the Fermi Large Area Telescope have used single sided silicon strip detectors to measure the position of incident gamma-rays with high resolution. At lower energies, two dimensional position information within a single detector is required. This talk investigates the use of monolithic CMOS active pixel silicon sensors –AstroPix – as a novel technology for use in future gamma-ray telescopes. Based upon detectors designed for use in the ATLAS detector at the LHC, AstroPix has the potential to maintain the high energy and angular resolution required of a medium-energy gamma-ray telescope while reducing noise with the dual detection and readout capabilities of a CMOS chip. The status of AstroPix development and testing, as well as outlook for application in future telescopes such as the proposed medium-energy gamma-ray telescope AMEGO-X, will be presented.
NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.
Switching and amplifying characteristics of a newly developed monolithic InGaAs Active Pixel Imager Array are presented. The sensor array is fabricated from InGaAs material epitaxially deposited on an InP substrate.
Modulation Transfer Function (MTF) is an important figure of merit in focal plane array sensors, especially for accurate target positions such as star trackers.
Synthetic Foveal imaging Technology (SyFT) is an emerging discipline of image capture and image-data processing that offers the prospect of greatly increased capabilities for real-time processing of large, high-resolution images (including mosaic images) for such purposes as automated recognition and tracking of moving objects of interest. SyFT offers a solution to the image-data processing problem arising from the proposed development of gigapixel mosaic focal-plane image-detector assemblies for very wide field-of-view imaging with high resolution for detecting and tracking sparse objects or events within narrow subfields of view. In order to identify and track the objects or events without the means of dynamic adaptation to be afforded by SyFT, it would be necessary to post-process data from an image-data space consisting of terabytes of data. Such post-processing would be time-consuming and, as a consequence, could result in missing significant events that could not be observed at all due to the time evolution of such events or could not be observed at required levels of fidelity without such real-time adaptations as adjusting focal-plane operating conditions or aiming of the focal plane in different directions to track such events. The basic concept of foveal imaging is straightforward: In imitation of a natural eye, a foveal-vision image sensor is designed to offer higher resolution in a small region of interest (ROI) within its field of view. Foveal vision reduces the amount of unwanted information that must be transferred from the image sensor to external image-data-processing circuitry. The aforementioned basic concept is not new in itself: indeed, image sensors based on these concepts have been described in several previous NASA Tech Briefs articles. Active-pixel integrated-circuit image sensors that can be programmed in real time to effect foveal artificial vision on demand are one such example. What is new in SyFT is a synergistic combination of recent advances in foveal imaging, computing, and related fields, along with a generalization of the basic foveal-vision concept to admit a synthetic fovea that is not restricted to one contiguous region of an image.
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The first innovative Visible Infrared Imaging Radiometer Suite (VIIRS) sensor aboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been in operation for 10 years since its launch on 28 October 2011. The second VIIRS sensor aboard the first Join Polar Satellite System (JPSS-1) satellite has been in operation for 4 years since its launch on 18 November 2017, which became NOAA-20. Well-geolocated and radiometrically calibrated Level-1 sensor data records (SDRs) from VIIRS are crucial to numerical weather prediction (NWP) and Level-2+ environmental data record (EDR) algorithms and products. The high quality of Level-2+ EDRs is a requirement for the continuity of NASA Earth science data records (ESDRs) and climate data records (CDRs), one of the two objectives of the SNPP mission and one of the three elements in the JPSS mission objective. The other objective of the SNPP mission is risk reduction for the follow-on JPSS missions. This paper summarizes the on-orbit geolocation calibration and validation (Cal/Val) activities for both VIIRS sensors onboard SNPP and NOAA-20 in the past 10 years. These activities include nominal geolocation Cal/Val activities, risk reduction activities, and improvements for the on-orbit VIIRS sensor operations. After these activities, sub-pixel geolocation accuracy is achieved. Nadir equivalent geolocation uncertainty is generally within 75 m (1-σ), or 20% imagery band pixels, in either the along-scan or along-track direction for both SNPP and NOAA-20 VIIRS sensors. The worst 16-day measured geolocation errors (radial, 3-σ) are 280 m and 267 m, respectively, in the latest SNPP and NOAA-20 VIIRS data collections, which are better than the required accuracy of 375 m (radial, 3-σ). The risk reduction activities also improved VIIRS builds for JPSS-3 and JPSS-4 satellites, and provide lessons learned for other VIIRS-like sensor builds.
To cope with the challenging environment of the planned high luminosity upgrade of the Large Hadron Collider (HL-LHC), scheduled to start operation in 2029, CMS will replace its entire tracking system. The requirements for the tracker are largely determined by the long operation time of 10 years with an instantaneous peak luminosity of up to 7.5 × 10 34 cm –2 s –1 in the ultimate performance scenario. Depending on the radial distance from the interaction point, the silicon sensors will receive a particle fluence corresponding to a non-ionizing energy loss of up to $\Phi_{\text {eq}}$ = 3.5 × 10 16 cm –2 . Here this paper focuses on planar pixel sensor design and qualification up to a fluence of $\Phi_{\text {eq}}$ = 1.4 × 10 16 cm –2 . For the development of appropriate planar pixel sensors an R&D program was initiated, which includes $n^+ -p$ sensors on 150 mm (6”) wafers with an active thickness of 150 μm with pixel sizes of 100 × 25 μm 2 and 50 × 50 μm 2 manufactured by Hamamatsu. Single chip modules with ROC4Sens and RD53A readout chips were made. Irradiation with protons and neutrons, as well was an extensive test beam campaign at DESY were carried out. This paper presents the investigation of various assemblies mainly with ROC4Sens readout chips. It demonstrates that multiple designs fulfill the requirements in terms of breakdown voltage, leakage current and efficiency. The single point resolution for 50 × 50 μm 2 pixels is measured as 4.0 μm for non-irradiated samples, and 6.3 μm after irradiation to $\Phi_{\text {eq}}$ = 7.2 × 10 15 cm –2 .
A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.